11 citations · 19 across the 5 of their papers we have counts for
4 papers · 1 filter
Recalibration of Aleatoric and Epistemic Regression Uncertainty in Medical Imaging
Max-Heinrich Laves, Sontje Ihler, Jacob F. Fast +2
The consideration of predictive uncertainty in medical imaging with deep learning is of utmost importance. We apply estimation of both aleatoric and epistemic uncertainty by variat…
Uncertainty Estimation in Medical Image Denoising with Bayesian Deep Image Prior
Max-Heinrich Laves, Malte Tölle, Tobias Ortmaier
Uncertainty quantification in inverse medical imaging tasks with deep learning has received little attention. However, deep models trained on large data sets tend to hallucinate an…
Uncertainty Quantification in Computer-Aided Diagnosis: Make Your Model say "I don't know" for Ambiguous Cases
Max-Heinrich Laves, Sontje Ihler, Tobias Ortmaier
We evaluate two different methods for the integration of prediction uncertainty into diagnostic image classifiers to increase patient safety in deep learning. In the first method,…
Deformable Medical Image Registration Using a Randomly-Initialized CNN as Regularization Prior
Max-Heinrich Laves, Sontje Ihler, Tobias Ortmaier
We present deformable unsupervised medical image registration using a randomly-initialized deep convolutional neural network (CNN) as regularization prior. Conventional registratio…